Overview

Dataset statistics

Number of variables18
Number of observations195
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.6 KiB
Average record size in memory144.7 B

Variable types

Numeric17
Categorical1

Alerts

MDVP:Fo(Hz) is highly overall correlated with MDVP:Fhi(Hz) and 2 other fieldsHigh correlation
MDVP:Fhi(Hz) is highly overall correlated with MDVP:Fo(Hz)High correlation
MDVP:Flo(Hz) is highly overall correlated with statusHigh correlation
MDVP:Jitter(Abs) is highly overall correlated with MDVP:Fo(Hz) and 10 other fieldsHigh correlation
MDVP:PPQ is highly overall correlated with MDVP:Jitter(Abs) and 8 other fieldsHigh correlation
Jitter:DDP is highly overall correlated with MDVP:Jitter(Abs) and 8 other fieldsHigh correlation
MDVP:Shimmer is highly overall correlated with MDVP:Jitter(Abs) and 9 other fieldsHigh correlation
Shimmer:APQ3 is highly overall correlated with MDVP:Jitter(Abs) and 9 other fieldsHigh correlation
Shimmer:APQ5 is highly overall correlated with MDVP:Jitter(Abs) and 9 other fieldsHigh correlation
MDVP:APQ is highly overall correlated with MDVP:Jitter(Abs) and 10 other fieldsHigh correlation
NHR is highly overall correlated with MDVP:Jitter(Abs) and 10 other fieldsHigh correlation
HNR is highly overall correlated with MDVP:Jitter(Abs) and 9 other fieldsHigh correlation
RPDE is highly overall correlated with MDVP:Jitter(Abs) and 7 other fieldsHigh correlation
spread1 is highly overall correlated with MDVP:Jitter(Abs) and 11 other fieldsHigh correlation
spread2 is highly overall correlated with MDVP:APQ and 1 other fieldsHigh correlation
D2 is highly overall correlated with NHRHigh correlation
status is highly overall correlated with MDVP:Fo(Hz) and 2 other fieldsHigh correlation
MDVP:Fo(Hz) has unique valuesUnique
MDVP:Fhi(Hz) has unique valuesUnique
MDVP:Flo(Hz) has unique valuesUnique
HNR has unique valuesUnique
RPDE has unique valuesUnique
DFA has unique valuesUnique
spread1 has unique valuesUnique
D2 has unique valuesUnique

Reproduction

Analysis started2023-09-18 03:41:49.212259
Analysis finished2023-09-18 03:42:22.922121
Duration33.71 seconds
Software versionydata-profiling vv4.4.0
Download configurationconfig.json

Variables

MDVP:Fo(Hz)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.22864
Minimum88.333
Maximum260.105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:23.019273image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum88.333
5-th percentile101.8791
Q1117.572
median148.79
Q3182.769
95-th percentile236.5078
Maximum260.105
Range171.772
Interquartile range (IQR)65.197

Descriptive statistics

Standard deviation41.390065
Coefficient of variation (CV)0.26836821
Kurtosis-0.62789811
Mean154.22864
Median Absolute Deviation (MAD)31.786
Skewness0.59173746
Sum30074.585
Variance1713.1375
MonotonicityNot monotonic
2023-09-18T09:12:23.169778image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
119.992 1
 
0.5%
169.774 1
 
0.5%
156.239 1
 
0.5%
145.174 1
 
0.5%
138.145 1
 
0.5%
166.888 1
 
0.5%
119.031 1
 
0.5%
120.078 1
 
0.5%
120.289 1
 
0.5%
120.256 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
88.333 1
0.5%
91.904 1
0.5%
95.056 1
0.5%
95.385 1
0.5%
95.605 1
0.5%
95.73 1
0.5%
96.106 1
0.5%
98.804 1
0.5%
100.77 1
0.5%
100.96 1
0.5%
ValueCountFrequency (%)
260.105 1
0.5%
252.455 1
0.5%
245.51 1
0.5%
244.99 1
0.5%
243.439 1
0.5%
242.852 1
0.5%
241.404 1
0.5%
240.301 1
0.5%
237.323 1
0.5%
237.226 1
0.5%

MDVP:Fhi(Hz)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197.10492
Minimum102.145
Maximum592.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:23.325887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum102.145
5-th percentile115.8188
Q1134.8625
median175.829
Q3224.2055
95-th percentile410.6398
Maximum592.03
Range489.885
Interquartile range (IQR)89.343

Descriptive statistics

Standard deviation91.491548
Coefficient of variation (CV)0.46417689
Kurtosis7.6272412
Mean197.10492
Median Absolute Deviation (MAD)42.485
Skewness2.542146
Sum38435.459
Variance8370.7033
MonotonicityNot monotonic
2023-09-18T09:12:23.478425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
157.302 1
 
0.5%
191.759 1
 
0.5%
195.107 1
 
0.5%
198.109 1
 
0.5%
197.238 1
 
0.5%
198.966 1
 
0.5%
127.533 1
 
0.5%
126.632 1
 
0.5%
128.143 1
 
0.5%
125.306 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
102.145 1
0.5%
102.305 1
0.5%
107.715 1
0.5%
108.664 1
0.5%
110.019 1
0.5%
112.24 1
0.5%
112.777 1
0.5%
113.597 1
0.5%
113.84 1
0.5%
115.697 1
0.5%
ValueCountFrequency (%)
592.03 1
0.5%
588.518 1
0.5%
586.567 1
0.5%
581.289 1
0.5%
565.74 1
0.5%
492.892 1
0.5%
479.697 1
0.5%
450.247 1
0.5%
442.824 1
0.5%
442.557 1
0.5%

MDVP:Flo(Hz)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.32463
Minimum65.476
Maximum239.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:23.628806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum65.476
5-th percentile68.9464
Q184.291
median104.315
Q3140.0185
95-th percentile220.1949
Maximum239.17
Range173.694
Interquartile range (IQR)55.7275

Descriptive statistics

Standard deviation43.521413
Coefficient of variation (CV)0.37413756
Kurtosis0.65461452
Mean116.32463
Median Absolute Deviation (MAD)23.678
Skewness1.2173504
Sum22683.303
Variance1894.1134
MonotonicityNot monotonic
2023-09-18T09:12:23.775830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.997 1
 
0.5%
151.451 1
 
0.5%
79.82 1
 
0.5%
80.637 1
 
0.5%
81.114 1
 
0.5%
79.512 1
 
0.5%
109.216 1
 
0.5%
105.667 1
 
0.5%
100.209 1
 
0.5%
104.773 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
65.476 1
0.5%
65.75 1
0.5%
65.782 1
0.5%
65.809 1
0.5%
66.004 1
0.5%
66.157 1
0.5%
67.021 1
0.5%
67.343 1
0.5%
68.401 1
0.5%
68.623 1
0.5%
ValueCountFrequency (%)
239.17 1
0.5%
237.303 1
0.5%
232.483 1
0.5%
232.435 1
0.5%
231.848 1
0.5%
229.256 1
0.5%
227.911 1
0.5%
225.227 1
0.5%
223.634 1
0.5%
221.156 1
0.5%

MDVP:Jitter(Abs)
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3958974 × 10-5
Minimum7 × 10-6
Maximum0.00026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:23.912320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7 × 10-6
5-th percentile1 × 10-5
Q12 × 10-5
median3 × 10-5
Q36 × 10-5
95-th percentile0.0001
Maximum0.00026
Range0.000253
Interquartile range (IQR)4 × 10-5

Descriptive statistics

Standard deviation3.4821909 × 10-5
Coefficient of variation (CV)0.79214561
Kurtosis10.869043
Mean4.3958974 × 10-5
Median Absolute Deviation (MAD)1 × 10-5
Skewness2.6490714
Sum0.008572
Variance1.2125653 × 10-9
MonotonicityNot monotonic
2023-09-18T09:12:24.042324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3 × 10-546
23.6%
4 × 10-528
14.4%
2 × 10-528
14.4%
1 × 10-520
10.3%
5 × 10-517
 
8.7%
6 × 10-516
 
8.2%
8 × 10-59
 
4.6%
7 × 10-58
 
4.1%
9 × 10-55
 
2.6%
9 × 10-65
 
2.6%
Other values (9) 13
 
6.7%
ValueCountFrequency (%)
7 × 10-61
 
0.5%
9 × 10-65
 
2.6%
1 × 10-520
10.3%
2 × 10-528
14.4%
3 × 10-546
23.6%
4 × 10-528
14.4%
5 × 10-517
 
8.7%
6 × 10-516
 
8.2%
7 × 10-58
 
4.1%
8 × 10-59
 
4.6%
ValueCountFrequency (%)
0.00026 1
 
0.5%
0.00022 1
 
0.5%
0.00016 1
 
0.5%
0.00015 2
 
1.0%
0.00014 1
 
0.5%
0.00012 1
 
0.5%
0.00011 2
 
1.0%
0.0001 3
 
1.5%
9 × 10-55
2.6%
8 × 10-59
4.6%

MDVP:PPQ
Real number (ℝ)

HIGH CORRELATION 

Distinct165
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003446359
Minimum0.00092
Maximum0.01958
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:24.189973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.00092
5-th percentile0.001315
Q10.00186
median0.00269
Q30.003955
95-th percentile0.009083
Maximum0.01958
Range0.01866
Interquartile range (IQR)0.002095

Descriptive statistics

Standard deviation0.0027589766
Coefficient of variation (CV)0.80054825
Kurtosis11.963922
Mean0.003446359
Median Absolute Deviation (MAD)0.00094
Skewness3.0738925
Sum0.67204
Variance7.6119521 × 10-6
MonotonicityNot monotonic
2023-09-18T09:12:24.349656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00332 4
 
2.1%
0.00283 3
 
1.5%
0.00203 3
 
1.5%
0.00182 3
 
1.5%
0.00113 2
 
1.0%
0.00194 2
 
1.0%
0.00192 2
 
1.0%
0.00312 2
 
1.0%
0.00258 2
 
1.0%
0.0039 2
 
1.0%
Other values (155) 170
87.2%
ValueCountFrequency (%)
0.00092 1
0.5%
0.00096 1
0.5%
0.001 1
0.5%
0.00106 1
0.5%
0.00107 1
0.5%
0.00113 2
1.0%
0.00115 1
0.5%
0.00122 1
0.5%
0.00128 1
0.5%
0.00133 1
0.5%
ValueCountFrequency (%)
0.01958 1
0.5%
0.01699 1
0.5%
0.01628 1
0.5%
0.01522 1
0.5%
0.01154 1
0.5%
0.01027 1
0.5%
0.0099 1
0.5%
0.00963 1
0.5%
0.00946 1
0.5%
0.00909 1
0.5%

Jitter:DDP
Real number (ℝ)

HIGH CORRELATION 

Distinct180
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0099199487
Minimum0.00204
Maximum0.06433
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:24.516340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.00204
5-th percentile0.003354
Q10.004985
median0.00749
Q30.011505
95-th percentile0.026271
Maximum0.06433
Range0.06229
Interquartile range (IQR)0.00652

Descriptive statistics

Standard deviation0.0089033444
Coefficient of variation (CV)0.89751919
Kurtosis14.224762
Mean0.0099199487
Median Absolute Deviation (MAD)0.00293
Skewness3.3620584
Sum1.93439
Variance7.9269541 × 10-5
MonotonicityNot monotonic
2023-09-18T09:12:24.665887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00507 3
 
1.5%
0.01109 2
 
1.0%
0.0078 2
 
1.0%
0.0075 2
 
1.0%
0.00731 2
 
1.0%
0.00994 2
 
1.0%
0.00696 2
 
1.0%
0.01285 2
 
1.0%
0.00616 2
 
1.0%
0.00496 2
 
1.0%
Other values (170) 174
89.2%
ValueCountFrequency (%)
0.00204 1
0.5%
0.00225 1
0.5%
0.00229 1
0.5%
0.00276 1
0.5%
0.00278 1
0.5%
0.00283 1
0.5%
0.00301 1
0.5%
0.00314 1
0.5%
0.00315 1
0.5%
0.00327 1
0.5%
ValueCountFrequency (%)
0.06433 1
0.5%
0.05563 1
0.5%
0.05401 1
0.5%
0.04705 1
0.5%
0.03476 1
0.5%
0.03351 1
0.5%
0.03225 1
0.5%
0.02987 1
0.5%
0.02756 1
0.5%
0.02716 1
0.5%

MDVP:Shimmer
Real number (ℝ)

HIGH CORRELATION 

Distinct188
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.029709128
Minimum0.00954
Maximum0.11908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:24.826061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.00954
5-th percentile0.011211
Q10.016505
median0.02297
Q30.037885
95-th percentile0.067256
Maximum0.11908
Range0.10954
Interquartile range (IQR)0.02138

Descriptive statistics

Standard deviation0.018856932
Coefficient of variation (CV)0.63471845
Kurtosis3.2383081
Mean0.029709128
Median Absolute Deviation (MAD)0.00839
Skewness1.6664804
Sum5.79328
Variance0.00035558388
MonotonicityNot monotonic
2023-09-18T09:12:24.971367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02448 2
 
1.0%
0.03273 2
 
1.0%
0.01608 2
 
1.0%
0.01725 2
 
1.0%
0.02293 2
 
1.0%
0.0145 2
 
1.0%
0.01503 2
 
1.0%
0.01412 1
 
0.5%
0.04479 1
 
0.5%
0.02503 1
 
0.5%
Other values (178) 178
91.3%
ValueCountFrequency (%)
0.00954 1
0.5%
0.00958 1
0.5%
0.01015 1
0.5%
0.01022 1
0.5%
0.01024 1
0.5%
0.0103 1
0.5%
0.01033 1
0.5%
0.01043 1
0.5%
0.01064 1
0.5%
0.01098 1
0.5%
ValueCountFrequency (%)
0.11908 1
0.5%
0.09419 1
0.5%
0.09178 1
0.5%
0.08684 1
0.5%
0.08143 1
0.5%
0.07959 1
0.5%
0.0717 1
0.5%
0.07118 1
0.5%
0.06734 1
0.5%
0.06727 1
0.5%

Shimmer:APQ3
Real number (ℝ)

HIGH CORRELATION 

Distinct184
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.015664154
Minimum0.00455
Maximum0.05647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:25.121861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.00455
5-th percentile0.005368
Q10.008245
median0.01279
Q30.020265
95-th percentile0.036227
Maximum0.05647
Range0.05192
Interquartile range (IQR)0.01202

Descriptive statistics

Standard deviation0.010153162
Coefficient of variation (CV)0.64817811
Kurtosis2.7201516
Mean0.015664154
Median Absolute Deviation (MAD)0.0051
Skewness1.5805764
Sum3.05451
Variance0.00010308669
MonotonicityNot monotonic
2023-09-18T09:12:25.272339image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01441 2
 
1.0%
0.00829 2
 
1.0%
0.01277 2
 
1.0%
0.01484 2
 
1.0%
0.00728 2
 
1.0%
0.00469 2
 
1.0%
0.01579 2
 
1.0%
0.00633 2
 
1.0%
0.01284 2
 
1.0%
0.00522 2
 
1.0%
Other values (174) 175
89.7%
ValueCountFrequency (%)
0.00455 1
0.5%
0.00468 1
0.5%
0.00469 2
1.0%
0.00476 1
0.5%
0.0049 1
0.5%
0.00504 1
0.5%
0.00522 2
1.0%
0.00534 1
0.5%
0.00538 1
0.5%
0.00557 1
0.5%
ValueCountFrequency (%)
0.05647 1
0.5%
0.05551 1
0.5%
0.05358 1
0.5%
0.04421 1
0.5%
0.04284 1
0.5%
0.04016 1
0.5%
0.03804 1
0.5%
0.03788 1
0.5%
0.03671 1
0.5%
0.0365 1
0.5%

Shimmer:APQ5
Real number (ℝ)

HIGH CORRELATION 

Distinct189
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.017878256
Minimum0.0057
Maximum0.0794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:25.422160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0057
5-th percentile0.006383
Q10.00958
median0.01347
Q30.02238
95-th percentile0.042701
Maximum0.0794
Range0.0737
Interquartile range (IQR)0.0128

Descriptive statistics

Standard deviation0.012023706
Coefficient of variation (CV)0.67253234
Kurtosis3.8742097
Mean0.017878256
Median Absolute Deviation (MAD)0.00468
Skewness1.7986971
Sum3.48626
Variance0.00014456949
MonotonicityNot monotonic
2023-09-18T09:12:25.574206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01219 2
 
1.0%
0.01024 2
 
1.0%
0.00747 2
 
1.0%
0.00972 2
 
1.0%
0.0116 2
 
1.0%
0.01144 2
 
1.0%
0.00621 1
 
0.5%
0.01805 1
 
0.5%
0.01859 1
 
0.5%
0.0057 1
 
0.5%
Other values (179) 179
91.8%
ValueCountFrequency (%)
0.0057 1
0.5%
0.00576 1
0.5%
0.00582 1
0.5%
0.00588 1
0.5%
0.00606 1
0.5%
0.0061 1
0.5%
0.00621 1
0.5%
0.0063 1
0.5%
0.00631 1
0.5%
0.00632 1
0.5%
ValueCountFrequency (%)
0.0794 1
0.5%
0.05556 1
0.5%
0.05426 1
0.5%
0.05005 1
0.5%
0.04962 1
0.5%
0.04825 1
0.5%
0.04791 1
0.5%
0.0458 1
0.5%
0.04518 1
0.5%
0.04282 1
0.5%

MDVP:APQ
Real number (ℝ)

HIGH CORRELATION 

Distinct189
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.024081487
Minimum0.00719
Maximum0.13778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:25.731343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.00719
5-th percentile0.009114
Q10.01308
median0.01826
Q30.0294
95-th percentile0.057718
Maximum0.13778
Range0.13059
Interquartile range (IQR)0.01632

Descriptive statistics

Standard deviation0.016946736
Coefficient of variation (CV)0.70372465
Kurtosis11.163288
Mean0.024081487
Median Absolute Deviation (MAD)0.00636
Skewness2.6180465
Sum4.69589
Variance0.00028719187
MonotonicityNot monotonic
2023-09-18T09:12:25.887311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01234 2
 
1.0%
0.03772 2
 
1.0%
0.00903 2
 
1.0%
0.01491 2
 
1.0%
0.01133 2
 
1.0%
0.0114 2
 
1.0%
0.03316 1
 
0.5%
0.02259 1
 
0.5%
0.02301 1
 
0.5%
0.00811 1
 
0.5%
Other values (179) 179
91.8%
ValueCountFrequency (%)
0.00719 1
0.5%
0.00726 1
0.5%
0.00762 1
0.5%
0.00802 1
0.5%
0.00811 1
0.5%
0.0086 1
0.5%
0.00871 1
0.5%
0.00882 1
0.5%
0.00903 2
1.0%
0.00915 1
0.5%
ValueCountFrequency (%)
0.13778 1
0.5%
0.08808 1
0.5%
0.08318 1
0.5%
0.06824 1
0.5%
0.0646 1
0.5%
0.06359 1
0.5%
0.06259 1
0.5%
0.06196 1
0.5%
0.06023 1
0.5%
0.05783 1
0.5%

NHR
Real number (ℝ)

HIGH CORRELATION 

Distinct185
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.024847077
Minimum0.00065
Maximum0.31482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:26.045664image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.00065
5-th percentile0.002528
Q10.005925
median0.01166
Q30.02564
95-th percentile0.092044
Maximum0.31482
Range0.31417
Interquartile range (IQR)0.019715

Descriptive statistics

Standard deviation0.040418449
Coefficient of variation (CV)1.6266883
Kurtosis21.994974
Mean0.024847077
Median Absolute Deviation (MAD)0.0069
Skewness4.2207091
Sum4.84518
Variance0.001633651
MonotonicityNot monotonic
2023-09-18T09:12:26.194730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.07223 2
 
1.0%
0.00476 2
 
1.0%
0.00839 2
 
1.0%
0.00231 2
 
1.0%
0.0062 2
 
1.0%
0.0042 2
 
1.0%
0.0034 2
 
1.0%
0.00681 2
 
1.0%
0.00479 2
 
1.0%
0.01049 2
 
1.0%
Other values (175) 175
89.7%
ValueCountFrequency (%)
0.00065 1
0.5%
0.00072 1
0.5%
0.00119 1
0.5%
0.00135 1
0.5%
0.00167 1
0.5%
0.00231 2
1.0%
0.00233 1
0.5%
0.00238 1
0.5%
0.00243 1
0.5%
0.00257 1
0.5%
ValueCountFrequency (%)
0.31482 1
0.5%
0.2593 1
0.5%
0.21713 1
0.5%
0.16744 1
0.5%
0.16265 1
0.5%
0.11843 1
0.5%
0.10952 1
0.5%
0.10748 1
0.5%
0.10715 1
0.5%
0.10323 1
0.5%

HNR
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.885974
Minimum8.441
Maximum33.047
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:26.349921image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum8.441
5-th percentile13.4838
Q119.198
median22.085
Q325.0755
95-th percentile26.9742
Maximum33.047
Range24.606
Interquartile range (IQR)5.8775

Descriptive statistics

Standard deviation4.4257643
Coefficient of variation (CV)0.2022192
Kurtosis0.61603583
Mean21.885974
Median Absolute Deviation (MAD)2.945
Skewness-0.5143175
Sum4267.765
Variance19.587389
MonotonicityNot monotonic
2023-09-18T09:12:26.501040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.033 1
 
0.5%
12.359 1
 
0.5%
19.196 1
 
0.5%
18.857 1
 
0.5%
18.178 1
 
0.5%
18.33 1
 
0.5%
26.842 1
 
0.5%
26.369 1
 
0.5%
23.949 1
 
0.5%
26.017 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
8.441 1
0.5%
8.867 1
0.5%
9.449 1
0.5%
10.489 1
0.5%
11.744 1
0.5%
11.866 1
0.5%
12.298 1
0.5%
12.359 1
0.5%
12.435 1
0.5%
12.529 1
0.5%
ValueCountFrequency (%)
33.047 1
0.5%
32.684 1
0.5%
31.732 1
0.5%
30.94 1
0.5%
30.775 1
0.5%
29.928 1
0.5%
29.746 1
0.5%
28.409 1
0.5%
27.421 1
0.5%
27.166 1
0.5%

status
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
147 
0
48 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters195
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 147
75.4%
0 48
 
24.6%

Length

2023-09-18T09:12:26.637534image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-18T09:12:26.772960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 147
75.4%
0 48
 
24.6%

Most occurring characters

ValueCountFrequency (%)
1 147
75.4%
0 48
 
24.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 147
75.4%
0 48
 
24.6%

Most occurring scripts

ValueCountFrequency (%)
Common 195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 147
75.4%
0 48
 
24.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 147
75.4%
0 48
 
24.6%

RPDE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49853554
Minimum0.25657
Maximum0.685151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:26.899359image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.25657
5-th percentile0.3309287
Q10.421306
median0.495954
Q30.5875625
95-th percentile0.6532203
Maximum0.685151
Range0.428581
Interquartile range (IQR)0.1662565

Descriptive statistics

Standard deviation0.10394171
Coefficient of variation (CV)0.20849409
Kurtosis-0.92178098
Mean0.49853554
Median Absolute Deviation (MAD)0.082659
Skewness-0.14340241
Sum97.21443
Variance0.01080388
MonotonicityNot monotonic
2023-09-18T09:12:27.048109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.414783 1
 
0.5%
0.56161 1
 
0.5%
0.618663 1
 
0.5%
0.637518 1
 
0.5%
0.623209 1
 
0.5%
0.585169 1
 
0.5%
0.457541 1
 
0.5%
0.491345 1
 
0.5%
0.46716 1
 
0.5%
0.468621 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
0.25657 1
0.5%
0.263654 1
0.5%
0.27685 1
0.5%
0.296888 1
0.5%
0.305062 1
0.5%
0.305429 1
0.5%
0.306443 1
0.5%
0.311369 1
0.5%
0.32648 1
0.5%
0.329577 1
0.5%
ValueCountFrequency (%)
0.685151 1
0.5%
0.677131 1
0.5%
0.671378 1
0.5%
0.671299 1
0.5%
0.665318 1
0.5%
0.663842 1
0.5%
0.660125 1
0.5%
0.654945 1
0.5%
0.653427 1
0.5%
0.65341 1
0.5%

DFA
Real number (ℝ)

UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.71809905
Minimum0.574282
Maximum0.825288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:27.195422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.574282
5-th percentile0.6323376
Q10.6747575
median0.722254
Q30.7618815
95-th percentile0.8160376
Maximum0.825288
Range0.251006
Interquartile range (IQR)0.087124

Descriptive statistics

Standard deviation0.05533583
Coefficient of variation (CV)0.077058772
Kurtosis-0.68615185
Mean0.71809905
Median Absolute Deviation (MAD)0.043369
Skewness-0.033213661
Sum140.02931
Variance0.0030620541
MonotonicityNot monotonic
2023-09-18T09:12:27.346466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.815285 1
 
0.5%
0.793509 1
 
0.5%
0.728421 1
 
0.5%
0.735546 1
 
0.5%
0.738245 1
 
0.5%
0.736964 1
 
0.5%
0.699787 1
 
0.5%
0.718839 1
 
0.5%
0.724045 1
 
0.5%
0.735136 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
0.574282 1
0.5%
0.58271 1
0.5%
0.605417 1
0.5%
0.623731 1
0.5%
0.62671 1
0.5%
0.627337 1
0.5%
0.628058 1
0.5%
0.628232 1
0.5%
0.630409 1
0.5%
0.631653 1
0.5%
ValueCountFrequency (%)
0.825288 1
0.5%
0.825069 1
0.5%
0.823484 1
0.5%
0.821364 1
0.5%
0.819521 1
0.5%
0.819235 1
0.5%
0.819032 1
0.5%
0.817756 1
0.5%
0.817396 1
0.5%
0.81634 1
0.5%

spread1
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-5.6843967
Minimum-7.964984
Maximum-2.434031
Zeros0
Zeros (%)0.0%
Negative195
Negative (%)100.0%
Memory size1.7 KiB
2023-09-18T09:12:27.495018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-7.964984
5-th percentile-7.306315
Q1-6.450096
median-5.720868
Q3-5.046192
95-th percentile-3.7336141
Maximum-2.434031
Range5.530953
Interquartile range (IQR)1.403904

Descriptive statistics

Standard deviation1.0902078
Coefficient of variation (CV)-0.19178953
Kurtosis-0.050199182
Mean-5.6843967
Median Absolute Deviation (MAD)0.71853
Skewness0.43213893
Sum-1108.4574
Variance1.188553
MonotonicityNot monotonic
2023-09-18T09:12:27.639582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.813031 1
 
0.5%
-3.297668 1
 
0.5%
-5.944191 1
 
0.5%
-5.594275 1
 
0.5%
-5.540351 1
 
0.5%
-5.825257 1
 
0.5%
-6.890021 1
 
0.5%
-5.892061 1
 
0.5%
-6.135296 1
 
0.5%
-6.112667 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
-7.964984 1
0.5%
-7.777685 1
0.5%
-7.695734 1
0.5%
-7.682587 1
0.5%
-7.517934 1
0.5%
-7.496264 1
0.5%
-7.3483 1
0.5%
-7.31951 1
0.5%
-7.314237 1
0.5%
-7.31055 1
0.5%
ValueCountFrequency (%)
-2.434031 1
0.5%
-2.839756 1
0.5%
-2.929379 1
0.5%
-2.93107 1
0.5%
-3.269487 1
0.5%
-3.297668 1
0.5%
-3.377325 1
0.5%
-3.444478 1
0.5%
-3.583722 1
0.5%
-3.700544 1
0.5%

spread2
Real number (ℝ)

HIGH CORRELATION 

Distinct194
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22651035
Minimum0.006274
Maximum0.450493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:27.793643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.006274
5-th percentile0.0888389
Q10.1743505
median0.218885
Q30.279234
95-th percentile0.3731391
Maximum0.450493
Range0.444219
Interquartile range (IQR)0.1048835

Descriptive statistics

Standard deviation0.083405763
Coefficient of variation (CV)0.36822054
Kurtosis-0.083022893
Mean0.22651035
Median Absolute Deviation (MAD)0.048702
Skewness0.14443049
Sum44.169518
Variance0.0069565212
MonotonicityNot monotonic
2023-09-18T09:12:27.943005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.210279 2
 
1.0%
0.266482 1
 
0.5%
0.320385 1
 
0.5%
0.12795 1
 
0.5%
0.087165 1
 
0.5%
0.115697 1
 
0.5%
0.152941 1
 
0.5%
0.195976 1
 
0.5%
0.20363 1
 
0.5%
0.217013 1
 
0.5%
Other values (184) 184
94.4%
ValueCountFrequency (%)
0.006274 1
0.5%
0.018689 1
0.5%
0.056844 1
0.5%
0.063412 1
0.5%
0.066994 1
0.5%
0.073298 1
0.5%
0.078202 1
0.5%
0.086372 1
0.5%
0.087165 1
0.5%
0.08784 1
0.5%
ValueCountFrequency (%)
0.450493 1
0.5%
0.434326 1
0.5%
0.414758 1
0.5%
0.397749 1
0.5%
0.396746 1
0.5%
0.393056 1
0.5%
0.391002 1
0.5%
0.389295 1
0.5%
0.389232 1
0.5%
0.375531 1
0.5%

D2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3818261
Minimum1.423287
Maximum3.671155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-09-18T09:12:28.097720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.423287
5-th percentile1.8487408
Q12.0991255
median2.361532
Q32.636456
95-th percentile3.0849315
Maximum3.671155
Range2.247868
Interquartile range (IQR)0.5373305

Descriptive statistics

Standard deviation0.38279905
Coefficient of variation (CV)0.16071662
Kurtosis0.2203341
Mean2.3818261
Median Absolute Deviation (MAD)0.271094
Skewness0.43038389
Sum464.45609
Variance0.14653511
MonotonicityNot monotonic
2023-09-18T09:12:28.246840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.301442 1
 
0.5%
3.413649 1
 
0.5%
1.929715 1
 
0.5%
1.765957 1
 
0.5%
1.821297 1
 
0.5%
1.996146 1
 
0.5%
2.328513 1
 
0.5%
2.108873 1
 
0.5%
2.539724 1
 
0.5%
2.527742 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
1.423287 1
0.5%
1.512275 1
0.5%
1.544609 1
0.5%
1.743867 1
0.5%
1.765957 1
0.5%
1.777901 1
0.5%
1.821297 1
0.5%
1.827012 1
0.5%
1.831691 1
0.5%
1.840198 1
0.5%
ValueCountFrequency (%)
3.671155 1
0.5%
3.413649 1
0.5%
3.317586 1
0.5%
3.274865 1
0.5%
3.184027 1
0.5%
3.142364 1
0.5%
3.13655 1
0.5%
3.10901 1
0.5%
3.099301 1
0.5%
3.098256 1
0.5%

Interactions

2023-09-18T09:12:20.663846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:49.706459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:51.577773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:53.421271image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:55.295583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:57.688832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:59.673220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:01.555053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:03.410679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:05.253167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:07.187904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:09.071357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:10.960431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:12.768964image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:14.578269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:16.943139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:18.836670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:20.770468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:49.820244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:51.686972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:53.532732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:55.407866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:57.807232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:59.784033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2023-09-18T09:12:22.063234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:51.155954image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:53.005024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:54.872172image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:57.258182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:59.222984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:01.128443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:02.990026image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:04.842911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:06.748969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:08.646058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:10.538792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:12.365246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:14.169540image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:16.534109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:18.393634image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:20.255429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:22.164447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:51.259985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:53.108642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:54.977331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:57.365031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:59.335210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:01.234274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:03.093594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:04.944236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:06.858505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:08.753316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:10.644442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:12.466422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:14.270853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:16.633745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:18.497491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:20.357041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:22.269609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:51.367281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:53.215740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:55.085946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:57.476142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:59.448994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:01.344648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:03.202409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:05.049449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:06.972034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:08.861097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:10.751740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:12.570373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:14.375295image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:16.740886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:18.602880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:20.462301image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:22.370552image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:51.472661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:53.319076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:55.191825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:57.582427image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:11:59.561398image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:01.449872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:03.306982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:05.151506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:07.080489image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:08.966701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:10.856453image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:12.670347image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:14.477795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:16.841491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:18.716161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-18T09:12:20.562665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-09-18T09:12:28.383082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
MDVP:Fo(Hz)MDVP:Fhi(Hz)MDVP:Flo(Hz)MDVP:Jitter(Abs)MDVP:PPQJitter:DDPMDVP:ShimmerShimmer:APQ3Shimmer:APQ5MDVP:APQNHRHNRRPDEDFAspread1spread2D2status
MDVP:Fo(Hz)1.0000.7960.324-0.566-0.298-0.197-0.164-0.145-0.130-0.229-0.1060.057-0.374-0.420-0.426-0.2270.2520.577
MDVP:Fhi(Hz)0.7961.0000.096-0.363-0.118-0.070-0.085-0.092-0.059-0.1160.060-0.022-0.223-0.463-0.256-0.1160.2610.393
MDVP:Flo(Hz)0.3240.0961.000-0.408-0.375-0.362-0.255-0.206-0.221-0.306-0.4580.258-0.3490.122-0.355-0.145-0.1330.523
MDVP:Jitter(Abs)-0.566-0.363-0.4081.0000.9100.8600.6640.6290.6240.6910.702-0.6240.5350.3220.8030.4730.2320.305
MDVP:PPQ-0.298-0.118-0.3750.9101.0000.9660.7620.7290.7520.7630.784-0.7660.4830.2600.7940.4310.3460.313
Jitter:DDP-0.197-0.070-0.3620.8600.9661.0000.7390.7160.7250.7180.801-0.7540.4250.1830.7160.3460.3800.245
MDVP:Shimmer-0.164-0.085-0.2550.6640.7620.7391.0000.9890.9870.9720.770-0.8660.5380.1720.6610.4440.4220.406
Shimmer:APQ3-0.145-0.092-0.2060.6290.7290.7160.9891.0000.9780.9380.728-0.8580.5110.1850.6190.4000.3890.348
Shimmer:APQ5-0.130-0.059-0.2210.6240.7520.7250.9870.9781.0000.9590.740-0.8650.5100.1870.6450.4000.4100.428
MDVP:APQ-0.229-0.116-0.3060.6910.7630.7180.9720.9380.9591.0000.779-0.8380.5890.1760.7130.5100.4360.429
NHR-0.1060.060-0.4580.7020.7840.8010.7700.7280.7400.7791.000-0.8660.619-0.1760.6590.4180.5700.000
HNR0.057-0.0220.258-0.624-0.766-0.754-0.866-0.858-0.865-0.838-0.8661.000-0.6220.010-0.628-0.374-0.4850.373
RPDE-0.374-0.223-0.3490.5350.4830.4250.5380.5110.5100.5890.619-0.6221.000-0.1290.5990.4490.2010.328
DFA-0.420-0.4630.1220.3220.2600.1830.1720.1850.1870.176-0.1760.010-0.1291.0000.2110.200-0.1950.341
spread1-0.426-0.256-0.3550.8030.7940.7160.6610.6190.6450.7130.659-0.6280.5990.2111.0000.6500.4240.599
spread2-0.227-0.116-0.1450.4730.4310.3460.4440.4000.4000.5100.418-0.3740.4490.2000.6501.0000.4840.453
D20.2520.261-0.1330.2320.3460.3800.4220.3890.4100.4360.570-0.4850.201-0.1950.4240.4841.0000.312
status0.5770.3930.5230.3050.3130.2450.4060.3480.4280.4290.0000.3730.3280.3410.5990.4530.3121.000

Missing values

2023-09-18T09:12:22.534053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-09-18T09:12:22.813981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

MDVP:Fo(Hz)MDVP:Fhi(Hz)MDVP:Flo(Hz)MDVP:Jitter(Abs)MDVP:PPQJitter:DDPMDVP:ShimmerShimmer:APQ3Shimmer:APQ5MDVP:APQNHRHNRstatusRPDEDFAspread1spread2D2
0119.992157.30274.9970.000070.005540.011090.043740.021820.031300.029710.0221121.03310.4147830.815285-4.8130310.2664822.301442
1122.400148.650113.8190.000080.006960.013940.061340.031340.045180.043680.0192919.08510.4583590.819521-4.0751920.3355902.486855
2116.682131.111111.5550.000090.007810.016330.052330.027570.038580.035900.0130920.65110.4298950.825288-4.4431790.3111732.342259
3116.676137.871111.3660.000090.006980.015050.054920.029240.040050.037720.0135320.64410.4349690.819235-4.1175010.3341472.405554
4116.014141.781110.6550.000110.009080.019660.064250.034900.048250.044650.0176719.64910.4173560.823484-3.7477870.2345132.332180
5120.552131.162113.7870.000080.007500.013880.047010.023280.035260.032430.0122221.37810.4155640.825069-4.2428670.2991112.187560
6120.267137.244114.8200.000030.002020.004660.016080.007790.009370.013510.0060724.88610.5960400.764112-5.6343220.2576821.854785
7107.332113.840104.3150.000030.001820.004310.015670.008290.009460.012560.0034426.89210.6374200.763262-6.1676030.1837212.064693
895.730132.06891.7540.000060.003320.008800.020930.010730.012770.017170.0107021.81210.6155510.773587-5.4986780.3277692.322511
995.056120.10391.2260.000060.003320.008030.028380.014410.017250.024440.0102221.86210.5470370.798463-5.0118790.3259962.432792
MDVP:Fo(Hz)MDVP:Fhi(Hz)MDVP:Flo(Hz)MDVP:Jitter(Abs)MDVP:PPQJitter:DDPMDVP:ShimmerShimmer:APQ3Shimmer:APQ5MDVP:APQNHRHNRstatusRPDEDFAspread1spread2D2
185116.286177.29196.9830.000030.001920.004030.015640.006670.009900.016910.0073724.19900.5985150.654331-5.5925840.1339172.058658
186116.556592.03086.2280.000040.002630.007620.016600.008200.009720.014910.0139723.95800.5664240.667654-6.4311190.1533102.161936
187116.342581.28994.2460.000020.001480.003450.013000.006310.007890.011440.0068025.02300.5284850.663884-6.3590180.1166362.152083
188114.563119.16786.6470.000030.001840.004390.011850.005570.007210.010950.0070324.77500.5553030.659132-6.7102190.1496941.913990
189201.774262.70778.2280.000030.003960.012350.025740.014540.015820.017580.0444119.36800.5084790.683761-6.9344740.1598902.316346
190174.188230.97894.2610.000030.002590.007900.040870.023360.024980.027450.0276419.51700.4484390.657899-6.5385860.1219522.657476
191209.516253.01789.4880.000030.002920.009940.027510.016040.016570.018790.0181019.14700.4316740.683244-6.1953250.1293032.784312
192174.688240.00574.2870.000080.005640.018730.023080.012680.013650.016670.1071517.88300.4075670.655683-6.7871970.1584532.679772
193198.764396.96174.9040.000040.003900.011090.022960.012650.013210.015880.0722319.02000.4512210.643956-6.7445770.2074542.138608
194214.289260.27777.9730.000030.003170.008850.018840.010260.011610.013730.0439821.20900.4628030.664357-5.7240560.1906672.555477